Engineer, Analytics

Ensemble Health Partners•Work at Home - Ohio - Other, OH

1d•$84,000 - $144,900•Remote

About The Position

The Analytics Engineer plays a critical role in transforming curated data into clear, consistent, and analytics ready‑ data models that power reporting, dashboards, and decision-making‑ across the organization. This role sits at the intersection of data engineering, analytics, and the business—owning the semantic layer, partnering closely with stakeholders, and ensuring that metrics are trusted, well-defined‑, and easy to use. The ideal candidate is deeply skilled in SQL based transformations and dimensional modeling, has strong business acumen, and is passionate about enabling analysts and leaders with high-quality, intuitive data.

Requirements

Bachelor’s degree in Computer Science, Data Analytics, Statistics, Mathematics, or a related field (or equivalent experience)
2+ years of experience in analytics engineering, analytics, business intelligence, or a related role.
2+ years of experience with Healthcare data including Revenue Cycle data
Experience with DBT
Advanced SQL expertise, with a strong track record of building complex, maintainable transformations.
Hands‑on experience with analytics engineering tools.
Strong understanding of dimensional modeling, metrics design, and semantic layer concepts.
Experience supporting BI tools and downstream analytics use cases (dashboards, reporting, ad hoc analysis).
Ability to communicate clearly with both technical and non‑technical stakeholders.
Experience in healthcare-related operations, with an understanding of industry processes and terminology.
Must be inquisitive and demonstrate openness to innovation including AI to explore better processes and ways to alleviate friction and improve patient and client experiences.

Responsibilities

Design, build, and maintain analytics ready‑ data models, including facts, dimensions, and data marts.
Develop and manage transformations primarily in the semantic and transformation layer using SQL based tooling
Define and maintain metrics, business logic, and calculations to ensure consistency across dashboards, reports, and analyses.
Apply dimensional modeling best practices optimized for BI and analytical consumption.
Partner closely with product, operations, finance, and business stakeholders to understand requirements and translate them into well-defined‑ data models and metrics.
Act as a steward of business logic—ensuring definitions are clear, documented, and aligned across teams.
Proactively identify gaps, ambiguities, or inconsistencies in metrics and drive alignment toward standardized definitions.
Optimize data models for clarity, usability, and performance for downstream consumers, including analysts and self-service‑ BI users.
Support analysts and BI developers by enabling faster, more reliable dashboard and report development.
Ensure analytics outputs are intuitive, discoverable, and trusted by decision‑makers.
Implement data quality checks and testing at the analytics layer to ensure accuracy and reliability.
Contribute to analytics engineering standards, conventions, and documentation.
Collaborate with data engineering partners to provide feedback on source data structure and readiness for analytics.